Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A portable Pythonic Data Catalog API powered by Ray that brings exabyte-level scalability and fast, ACID-compliant, change-data-capture to your big data workloads.

A toolkit to run Ray applications on Kubernetes

Tracking Ray Enhancement Proposals

Distributed XGBoost on Ray

Helm charts for the KubeRay project

Mobius is an AI infrastructure platform for distributed online learning, including online sample processing, training and serving.

LLMPerf is a library for validating and benchmarking LLMs